Robustness of energy landscape control for spin networks under decoherence

Quantum spin networks form a generic system to describe a range of quantum devices for quantum information processing and sensing applications. Understanding how to control them is essential to achieve devices with practical functionalities. Energy landscape shaping is a novel control paradigm to achieve selective transfer of excitations in a spin network with surprisingly strong robustness towards uncertainties in the Hamiltonians. Here we study the effect of decoherence, specifically generic pure dephasing, on the robustness of these controllers. Results indicate that while the effectiveness of the controllers is reduced by decoherence, certain controllers remain sufficiently effective, indicating potential to find highly effective controllers without exact knowledge of the decoherence processes.Comment: 6 pages, 6 figure

Binding energy and dephasing of biexcitons in In0.18Ga0.82As/GaAs single quantum wells

Biexciton binding energies and biexciton dephasing in In0.18Ga0.82As/GaAs single quantum wells have been measured by time-integrated and spectrally resolved four-wave mixing. The biexciton binding energy increases from 1.5 to 2.6 meV for well widths increasing from 1 to 4 nm. The ratio between exciton and biexciton binding energy changes from 0.23 to 0.3 with increasing inhomogeneous broadening, corresponding to increasing well width. From the temperature dependence of the exciton and biexciton four-wave mixing signal decay, we have deduced the acoustic-phonon scattering of the exciton-biexciton transition. It is found to be comparable to that of the exciton transition, indicating that the deformation potential interactions for the exciton and the exciton-biexciton transitions are comparable

Chemically-specific dual/differential CARS micro-spectroscopy of saturated and unsaturated lipid droplets

We have investigated the ability of dual-frequency Coherent Antistokes Raman Scattering (D-CARS) micro-spectroscopy, based on femtosecond pulses (100 fs or 5 fs) spectrally focussed by glass dispersion, to distinguish the chemical composition of micron-sized lipid droplets consisting of different triglycerides types (poly-unsaturated glyceryl trilinolenate, mono-unsaturated glyceryl trioleate and saturated glyceryl tricaprylate and glyceryl tristearate) in a rapid and label-free way. A systematic comparison of Raman spectra with CARS and D-CARS spectra was used to identify D-CARS spectral signatures which distinguish the disordered poly-unsaturated lipids from the more ordered saturated ones both in the CH-stretch vibration region and in the fingerprint region, without the need for lengthy CARS multiplex acquisition and analysis. D-CARS images of the lipid droplets at few selected wavenumbers clearly resolved the lipid composition differences, and exemplify the potential of this technique for label-free chemically selective rapid imaging of cytosolic lipid droplets in living cell

Coherence dynamics and quantum-to-classical crossover in an exciton-cavity system in the quantum strong coupling regime

Interaction between light and matter generates optical nonlinearities, which are particularly pronounced in the quantum strong coupling regime. When a single bosonic mode couples to a single fermionic mode, a Jaynes-Cummings (JC) ladder is formed, which we realize here using cavity photons and quantum dot excitons. We measure and model the coherent anharmonic response of this strongly coupled exciton-cavity system at resonance. Injecting two photons into the cavity, we demonstrate a root 2 larger polariton splitting with respect to the vacuum Rabi splitting. This is achieved using coherent nonlinear spectroscopy, specifically four-wave mixing, where the coherence between the ground state and the first (second) rung of the JC ladder can be interrogated for positive (negative) delays. With increasing excitation intensity and thus rising average number of injected photons, we observe spectral signatures of the quantum-to-classical crossover of the strong coupling regime.Peer reviewe

Reinforcement Learning vs. Gradient-Based Optimisation for Robust Energy Landscape Control of Spin-1/2 Quantum Networks

We explore the use of policy gradient methods in reinforcement learning for quantum control via energy landscape shaping of XX-Heisenberg spin chains in a model agnostic fashion. Their performance is compared to finding controllers using gradient-based L-BFGS optimisation with restarts, with full access to an analytical model. Hamiltonian noise and coarse-graining of fidelity measurements are considered. Reinforcement learning is able to tackle challenging, noisy quantum control problems where L-BFGS optimization algorithms struggle to perform well. Robustness analysis under different levels of Hamiltonian noise indicates that controllers found by reinforcement learning appear to be less affected by noise than those found with L-BFGS.Comment: 7 pages, 7 figure

One-dimensional dynamics of nearly unstable axisymmetric liquid bridges

A general one-dimensional model is considered that describes the dynamics of slender, axisymmetric, noncylindrical liquid bridges between two equal disks. Such model depends on two adjustable parameters and includes as particular cases the standard Lee and Cosserat models. For slender liquid bridges, the model provides sufficiently accurate results and involves much easier and faster calculations than the full three-dimensional model. In particular, viscous effects are easily accounted for. The one-dimensional model is used to derive a simple weakly nonlinear description of the dynamics near the instability limit. Small perturbations of marginal instability conditions are also considered that account for volume perturbations, nonequality of the supporting disks, and axial gravity. The analysis shows that the dynamics breaks the reflection symmetry on the midplane between the supporting disks. The weakly nonlinear evolution of the amplitude of the perturbation is given by a Duffing equation, whose coefficients are calculated in terms of the slenderness as a part of the analysis and exhibit a weak dependence on the adjustable parameters of the one-dimensional model. The amplitude equation is used to make quantitative predictions of both the (first stage of) breakage for unstable configurations and the (slow) dynamics for stable configurations

Monte Carlo simulations of spin transport in a strained nanoscale InGaAs field effect transistor

Spin-based logic devices could operate at very high speed with very low energy consumption and hold significant promise for quantum information processing and metrology. Here, an in-house developed, experimentally verified, ensemble self-consistent Monte Carlo device simulator with a Bloch equation model using a spin-orbit interaction Hamiltonian accounting for Dresselhaus and Rashba couplings is developed and applied to a spin field effect transistor (spinFET) operating under externally applied voltages on a gate and a drain. In particular, we simulate electron spin transport in a \SI{25}{nm} gate length \chem{In_{0.7}Ga_{0.3}As} metal-oxide-semiconductor field-effect transistor (MOSFET) with a CMOS compatible architecture. We observe non-uniform decay of the net magnetization between the source and gate and a magnetization recovery effect due to spin refocusing induced by a high electric field between the gate and drain. We demonstrate coherent control of the polarization vector of the drain current via the source-drain and gate voltages, and show that the magnetization of the drain current is strain-sensitive and can be increased twofold by strain induced into the channel

High-multipolar effects on the Casimir force: the non-retarded limit

We calculate exactly the Casimir force or dispersive force, in the non-retarded limit, between a spherical nanoparticle and a substrate beyond the London's or dipolar approximation. We find that the force is a non-monotonic function of the distance between the sphere and the substrate, such that, it is enhanced by several orders of magnitude as the sphere approaches the substrate. Our results do not agree with previous predictions like the Proximity theorem approach.Comment: 7 pages including 2 figures. Submitted to Europjysics Letter